refactor: MVC 구조 분리 + 미사용 파일 archive 정리

- tick_trader.py를 Controller로 축소, 로직을 3개 모듈로 분리: - core/signal.py: 시그널 감지, 지표 계산 (calc_vr, calc_atr, detect_signal) - core/order.py: Upbit 주문 실행 (매수/매도/취소/조회) - core/position_manager.py: 포지션 관리, DB sync, 복구, 청산 조건 - type hints, Google docstring, 구체적 예외 타입 적용 - 50줄 초과 함수 분리 (process_signal, restore_positions) - 미사용 파일 58개 archive/ 폴더로 이동 - README.md 추가 Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-03-06 20:46:47 +09:00
parent 976c53ed66
commit 6e0c4508fa
69 changed files with 5018 additions and 495 deletions
--- a/archive/tests/sim_recent_db.py
+++ b/archive/tests/sim_recent_db.py
@@ -0,0 +1,363 @@
+"""DB 기반 하이브리드 시뮬레이션 (신호=10분봉 / 스탑=1분봉).
+
+실행 흐름:
+  1. pyupbit에서 10분봉(300봉) + 1분봉(2880봉) fetch → BACKTEST_OHLCV upsert
+  2. BACKTEST_OHLCV에서 데이터 로드
+  3. 하이브리드 시뮬 실행
+     - 10분봉 타임인덱스로 신호 감지 / 진입
+     - 각 10분봉 구간 내 1분봉으로 트레일링스탑 체크
+  4. 결과 출력
+"""
+import sys
+import os
+sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
+from dotenv import load_dotenv
+load_dotenv(os.path.join(os.path.dirname(os.path.dirname(os.path.abspath(__file__))), '.env'))
+
+import time
+import pyupbit
+import pandas as pd
+import numpy as np
+import oracledb
+
+# ── Oracle 연결 ─────────────────────────────────────────────────────────────
+def _get_conn():
+    kwargs = dict(
+        user=os.environ["ORACLE_USER"],
+        password=os.environ["ORACLE_PASSWORD"],
+        dsn=os.environ["ORACLE_DSN"],
+    )
+    wallet = os.environ.get("ORACLE_WALLET")
+    if wallet:
+        kwargs["config_dir"] = wallet
+    return oracledb.connect(**kwargs)
+
+
+# ── 전략 파라미터 ────────────────────────────────────────────────────────────
+LOCAL_VOL_N   = 28
+QUIET_N       = 12
+QUIET_PCT     = 2.0
+THRESH        = 4.8
+SIGNAL_TO     = 48
+VOL_THRESH    = 6.0
+FNG           = 14
+ATR_N         = 28
+ATR_MULT      = 1.5
+ATR_MIN       = 0.010
+ATR_MAX       = 0.020
+TS_N          = 48
+TIME_STOP_PCT = 3.0
+BUDGET        = 15_000_000
+MAX_POS       = 3
+FEE           = 0.0005
+PER_POS       = BUDGET // MAX_POS
+
+TICKERS = [
+    'KRW-XRP','KRW-BTC','KRW-ETH','KRW-SOL','KRW-DOGE',
+    'KRW-ADA','KRW-SUI','KRW-NEAR','KRW-KAVA','KRW-SXP',
+    'KRW-AKT','KRW-SONIC','KRW-IP','KRW-ORBS','KRW-VIRTUAL',
+    'KRW-BARD','KRW-XPL','KRW-KITE','KRW-ENSO','KRW-0G',
+]
+
+SIM_START = '2026-03-03 00:00:00'
+SIM_END   = '2026-03-04 13:30:00'
+
+
+# ── BACKTEST_OHLCV 공통 함수 ─────────────────────────────────────────────────
+
+def upsert_ohlcv(conn, ticker: str, interval_cd: str, df: pd.DataFrame) -> int:
+    """DataFrame을 BACKTEST_OHLCV에 저장 (기존 TS 스킵). 반환: 신규 삽입 건수."""
+    cur = conn.cursor()
+    min_ts = df.index.min().to_pydatetime()
+    cur.execute(
+        "SELECT ts FROM backtest_ohlcv WHERE ticker=:t AND interval_cd=:iv AND ts >= :since",
+        {"t": ticker, "iv": interval_cd, "since": min_ts}
+    )
+    existing = {r[0] for r in cur.fetchall()}
+
+    new_rows = [
+        (ticker, interval_cd, ts_idx.to_pydatetime(),
+         float(row["open"]), float(row["high"]), float(row["low"]),
+         float(row["close"]), float(row["volume"]))
+        for ts_idx, row in df.iterrows()
+        if ts_idx.to_pydatetime() not in existing
+    ]
+    if not new_rows:
+        return 0
+
+    cur.executemany(
+        "INSERT INTO backtest_ohlcv (ticker, interval_cd, ts, open_p, high_p, low_p, close_p, volume_p) "
+        "VALUES (:1, :2, :3, :4, :5, :6, :7, :8)",
+        new_rows
+    )
+    conn.commit()
+    return len(new_rows)
+
+
+def load_from_db(conn, ticker: str, interval_cd: str, since: str):
+    """BACKTEST_OHLCV에서 ticker의 OHLCV 로드."""
+    cur = conn.cursor()
+    cur.execute(
+        "SELECT ts, open_p, high_p, low_p, close_p, volume_p "
+        "FROM backtest_ohlcv "
+        "WHERE ticker=:ticker AND interval_cd=:iv "
+        "AND ts >= TO_TIMESTAMP(:since, 'YYYY-MM-DD HH24:MI:SS') "
+        "ORDER BY ts",
+        {"ticker": ticker, "iv": interval_cd, "since": since}
+    )
+    rows = cur.fetchall()
+    if not rows:
+        return None
+    df = pd.DataFrame(rows, columns=["ts","open","high","low","close","volume"])
+    df["ts"] = pd.to_datetime(df["ts"])
+    df.set_index("ts", inplace=True)
+    return df.astype(float)
+
+
+# ── 1단계: DB 업데이트 ───────────────────────────────────────────────────────
+
+def refresh_db(conn) -> None:
+    """10분봉(300봉) + 1분봉(2880봉) fetch → BACKTEST_OHLCV upsert."""
+    print("BACKTEST_OHLCV 업데이트 중...", flush=True)
+    total10, total1 = 0, 0
+    for tk in TICKERS:
+        try:
+            # 10분봉
+            df10 = pyupbit.get_ohlcv(tk, interval='minute10', count=300)
+            if df10 is not None and len(df10) >= 10:
+                total10 += upsert_ohlcv(conn, tk, 'minute10', df10)
+            time.sleep(0.12)
+
+            # 1분봉 (2일치 ≈ 2880봉, 내부 자동 페이지네이션)
+            df1 = pyupbit.get_ohlcv(tk, interval='minute1', count=2880)
+            if df1 is not None and len(df1) >= 60:
+                total1 += upsert_ohlcv(conn, tk, 'minute1', df1)
+            time.sleep(0.15)
+
+            print(f"  {tk}: 10m={len(df10) if df10 is not None else 0}봉 / "
+                  f"1m={len(df1) if df1 is not None else 0}봉", flush=True)
+        except Exception as e:
+            print(f"  {tk} 오류: {e}")
+
+    print(f"DB 업데이트 완료: 10분봉 신규 {total10}행 / 1분봉 신규 {total1}행\n", flush=True)
+
+
+# ── ATR 계산 ────────────────────────────────────────────────────────────────
+
+def calc_atr(df, i, n=28):
+    start = max(0, i - n)
+    sub = df.iloc[start:i]
+    if len(sub) < 5:
+        return ATR_MIN
+    hi = sub['high'].values
+    lo = sub['low'].values
+    cl = sub['close'].values
+    tr = [max(hi[j]-lo[j], abs(hi[j]-cl[j-1]) if j>0 else 0,
+              abs(lo[j]-cl[j-1]) if j>0 else 0) for j in range(len(sub))]
+    atr_pct = np.mean(tr) / cl[-1] if cl[-1] > 0 else ATR_MIN
+    return max(ATR_MIN, min(ATR_MAX, atr_pct * ATR_MULT))
+
+
+# ── 하이브리드 시뮬 ──────────────────────────────────────────────────────────
+
+def run_sim(raw10: dict, raw1: dict) -> None:
+    """신호=10분봉 / 스탑=1분봉 하이브리드 시뮬."""
+
+    # 10분봉 공통 타임인덱스
+    all_idx10 = None
+    for df in raw10.values():
+        all_idx10 = df.index if all_idx10 is None else all_idx10.union(df.index)
+    all_idx10 = all_idx10.sort_values()
+    mask = (all_idx10 >= SIM_START) & (all_idx10 <= SIM_END)
+    sim_idx10 = all_idx10[mask]
+
+    if len(sim_idx10) == 0:
+        print("시뮬 구간 데이터 없음")
+        return
+
+    print(f"시뮬 구간(10분봉): {sim_idx10[0]} ~ {sim_idx10[-1]} ({len(sim_idx10)}봉)")
+    # 1분봉 커버리지 확인
+    n1m = sum(
+        len(df[(df.index >= SIM_START) & (df.index <= SIM_END)])
+        for df in raw1.values() if len(raw1) > 0
+    )
+    print(f"1분봉 총 {n1m}봉 (스탑 체크용)\n")
+
+    positions = {}  # ticker → {buy_price, peak, entry_i, invested, atr_stop}
+    signals   = {}  # ticker → {price, vol_r, sig_i}
+    trades    = []
+
+    for i, ts10 in enumerate(sim_idx10):
+        ts10_prev = sim_idx10[i - 1] if i > 0 else ts10
+
+        # ── 1) 1분봉으로 스탑 체크 ────────────────────────────────────────
+        for tk in list(positions.keys()):
+            pos = positions[tk]
+            # 진입 캔들 종료 전엔 체크 금지
+            # 10분봉 ts=X 는 [X, X+10min) 구간이므로 실제 진입은 X+9:59
+            # → X+10min 이후 1분봉부터 체크
+            entry_candle_end = sim_idx10[pos['entry_i']] + pd.Timedelta(minutes=10)
+
+            if tk not in raw1:
+                # 1분봉 없으면 10분봉 종가로 fallback (단, 진입 다음 봉부터)
+                if ts10 <= sim_idx10[pos['entry_i']]:
+                    continue
+                if tk not in raw10 or ts10 not in raw10[tk].index:
+                    continue
+                current = float(raw10[tk].loc[ts10, 'close'])
+                _check_stop(pos, tk, current, ts10, i, sim_idx10, trades, positions)
+                continue
+
+            df1 = raw1[tk]
+            # 진입 캔들 종료(entry_candle_end) 이후 + 현재 10분봉 구간 이내
+            mask1 = (df1.index >= entry_candle_end) & (df1.index > ts10_prev) & (df1.index <= ts10)
+            sub1 = df1[mask1]
+
+            for ts1m, row1m in sub1.iterrows():
+                current = float(row1m['close'])
+                if _check_stop(pos, tk, current, ts1m, i, sim_idx10, trades, positions):
+                    break  # 이미 청산됨
+
+        # ── 2) 신호 만료 ────────────────────────────────────────────────
+        for tk in list(signals.keys()):
+            if i - signals[tk]['sig_i'] > SIGNAL_TO:
+                del signals[tk]
+
+        # ── 3) 신호 감지 + 진입 (10분봉 기준) ──────────────────────────
+        for tk in TICKERS:
+            if tk in positions: continue
+            if len(positions) >= MAX_POS: break
+            if tk not in raw10: continue
+            df10 = raw10[tk]
+            if ts10 not in df10.index: continue
+            loc = df10.index.get_loc(ts10)
+            if loc < LOCAL_VOL_N + QUIET_N + 2: continue
+
+            vol_prev = float(df10['volume'].iloc[loc - 1])
+            vol_avg  = float(df10['volume'].iloc[loc - LOCAL_VOL_N - 1:loc - 1].mean())
+            vol_r    = vol_prev / vol_avg if vol_avg > 0 else 0.0
+            current  = float(df10['close'].iloc[loc])
+            close_qn = float(df10['close'].iloc[loc - QUIET_N])
+            chg      = abs(current - close_qn) / close_qn * 100 if close_qn > 0 else 999.0
+
+            if vol_r >= VOL_THRESH and chg < QUIET_PCT:
+                if tk not in signals or vol_r > signals[tk]['vol_r']:
+                    signals[tk] = {'price': current, 'vol_r': vol_r, 'sig_i': i}
+
+            if tk in signals:
+                sig_p = signals[tk]['price']
+                move  = (current - sig_p) / sig_p * 100
+                if move >= THRESH:
+                    atr_stop = calc_atr(df10, loc, ATR_N)
+                    positions[tk] = {
+                        'buy_price': current, 'peak': current,
+                        'entry_i': i, 'invested': PER_POS,
+                        'atr_stop': atr_stop,
+                    }
+                    del signals[tk]
+
+    # ── 미청산 강제 청산 ─────────────────────────────────────────────────────
+    last_ts10 = sim_idx10[-1]
+    for tk, pos in list(positions.items()):
+        if tk not in raw10: continue
+        df10 = raw10[tk]
+        current = float(df10.loc[last_ts10, 'close']) if last_ts10 in df10.index else pos['buy_price']
+        pnl = (current - pos['buy_price']) / pos['buy_price'] * 100
+        fee = pos['invested'] * FEE + current * (pos['invested']/pos['buy_price']) * FEE
+        krw = current * (pos['invested']/pos['buy_price']) - pos['invested'] - fee
+        trades.append({
+            'date': last_ts10.date(), 'ticker': tk,
+            'buy_price': pos['buy_price'], 'sell_price': current,
+            'pnl_pct': pnl, 'krw': krw, 'reason': '미청산(현재가)',
+            'entry_ts': sim_idx10[pos['entry_i']], 'exit_ts': last_ts10,
+        })
+
+    # ── 결과 출력 ────────────────────────────────────────────────────────────
+    if not trades:
+        print("거래 없음")
+        return
+
+    import collections
+    by_date = collections.defaultdict(list)
+    for t in trades:
+        by_date[t['date']].append(t)
+
+    total_krw, total_wins = 0, 0
+    for date in sorted(by_date.keys()):
+        day_trades = by_date[date]
+        day_krw  = sum(t['krw'] for t in day_trades)
+        day_wins = sum(1 for t in day_trades if t['pnl_pct'] > 0)
+        total_krw  += day_krw
+        total_wins += day_wins
+        print(f"\n{'='*62}")
+        print(f"【{date}】 {len(day_trades)}건 | 승률={day_wins/len(day_trades)*100:.0f}% | 일손익={day_krw:+,.0f}원")
+        print(f"{'='*62}")
+        for t in sorted(day_trades, key=lambda x: x['entry_ts']):
+            e = '✅' if t['pnl_pct'] > 0 else '❌'
+            print(f"  {e} {t['ticker']:12s} "
+                  f"매수={t['buy_price']:,.0f} @ {str(t['entry_ts'])[5:16]} → "
+                  f"매도={t['sell_price']:,.0f} @ {str(t['exit_ts'])[5:16]} "
+                  f"| {t['pnl_pct']:+.1f}% ({t['krw']:+,.0f}원) [{t['reason']}]")
+
+    print(f"\n{'='*62}")
+    print(f"【2일 합계】 {len(trades)}건 | "
+          f"승률={total_wins/len(trades)*100:.0f}% | 총손익={total_krw:+,.0f}원")
+    print(f"  [1분봉 스탑 시뮬] VOL≥{VOL_THRESH}x + 횡보<{QUIET_PCT}% → +{THRESH}% 진입 (F&G={FNG})")
+
+
+def _check_stop(pos, tk, current, ts, i, sim_idx10, trades, positions) -> bool:
+    """스탑 체크. 청산 시 True 반환."""
+    if current > pos['peak']:
+        pos['peak'] = current
+    age = i - pos['entry_i']
+    pnl = (current - pos['buy_price']) / pos['buy_price'] * 100
+    peak_drop = (pos['peak'] - current) / pos['peak'] * 100
+    atr_stop = pos['atr_stop']
+    reason = None
+    if peak_drop >= atr_stop * 100:
+        reason = f"트레일링스탑({atr_stop*100:.1f}%)"
+    elif age >= TS_N and pnl < TIME_STOP_PCT:
+        reason = f"타임스탑(+{pnl:.1f}%<{TIME_STOP_PCT}%)"
+    if reason:
+        fee = pos['invested'] * FEE + current * (pos['invested']/pos['buy_price']) * FEE
+        krw = current * (pos['invested']/pos['buy_price']) - pos['invested'] - fee
+        trades.append({
+            'date': ts.date() if hasattr(ts, 'date') else ts,
+            'ticker': tk,
+            'buy_price': pos['buy_price'], 'sell_price': current,
+            'pnl_pct': pnl, 'krw': krw, 'reason': reason,
+            'entry_ts': sim_idx10[pos['entry_i']], 'exit_ts': ts,
+        })
+        del positions[tk]
+        return True
+    return False
+
+
+# ── main ─────────────────────────────────────────────────────────────────────
+
+conn = _get_conn()
+
+# 1) DB 업데이트
+refresh_db(conn)
+
+# 2) DB에서 데이터 로드
+print("DB에서 OHLCV 로드 중...", flush=True)
+LOAD_SINCE = '2026-03-01 00:00:00'
+raw10, raw1 = {}, {}
+for tk in TICKERS:
+    df10 = load_from_db(conn, tk, 'minute10', LOAD_SINCE)
+    if df10 is not None and len(df10) > LOCAL_VOL_N + QUIET_N:
+        raw10[tk] = df10
+
+    df1 = load_from_db(conn, tk, 'minute1', LOAD_SINCE)
+    if df1 is not None and len(df1) > 60:
+        raw1[tk] = df1
+
+print(f"로드 완료: 10분봉 {len(raw10)}종목 / 1분봉 {len(raw1)}종목\n")
+conn.close()
+
+# 3) 시뮬 실행
+print("="*62)
+print(f"하이브리드 시뮬 (신호=10분봉 / 스탑=1분봉) | 2026-03-03 ~ 03-04")
+print("="*62)
+run_sim(raw10, raw1)